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Small Discussion About Spark MLlib?

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What is MLlib?

MLlib stands for Machine Learning Library (MLlib)

MLlib is Spark’s scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives, as outlined below:

  • Data types
  • Basic statistics
  • Classification and regression
  • Collaborative filtering
  • Clustering
  • Dimensionality reduction
  • Feature extraction and transformation
  • Optimization

Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface  centered on the RDD abstraction  This interface mirrors a functional/higher-order model of programming: a "driver" program invokes parallel operations such as map, filter or reduce on an RDD by passing a function to Spark, which then schedules the function's execution in parallel on the cluster.

These operations, and additional ones such as joins, take RDDs as input and produce new RDDs. RDDs are immutable and their operations are lazy; fault-tolerance is achieved by keeping track of the "lineage" of each RDD so that it can be reconstructed in the case of data loss. RDDs can contain any type of Python, Java, or Scala objects.​

The Video for MLlib Spark

posted Apr 30 by anonymous

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Video for Keras

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